class_docstr: Dual Attention Networks for Semantic Segmentation
  
  Parameters
  ----------
  nclass : int
      Number of categories for the training dataset.
  backbone : string
      Pre-trained dilated backbone network type (default:'resnet50'; 'resnet50',
      'resnet101').
  norm_layer : object
      Normalization layer used in backbone network (default: :class:`mxnet.gluon.nn.BatchNorm`;
  
  Reference:
      Jun Fu, Jing Liu, Haijie Tian, Yong Li, Yongjun Bao, Zhiwei Fang, Hanqing Lu. "Dual Attention
      Network for Scene Segmentation." *CVPR*, 2019
class_docstr_tok: ["Dual","Attention","Networks","for","Semantic","Segmentation","Parameters","--","--","--","--","--","nclass",":","int","Number","of","categories","for","the","training","dataset",".","backbone",":","string","Pre-trained","dilated","backbone","network","type","(","default",":","'resnet50","'",";","'resnet50","'",",","'resnet101","'",")",".","norm_layer",":","object","Normalization","layer","used","in","backbone","network","(","default",":",":","class",":","`","mxnet.gluon.nn.BatchNorm","`",";","Reference",":","Jun","Fu",",","Jing","Liu",",","Haijie","Tian",",","Yong","Li",",","Yongjun","Bao",",","Zhiwei","Fang",",","Hanqing","Lu",".","``","Dual","Attention","Network","for","Scene","Segmentation",".","''","*","CVPR","*",",","2019"]
code: def hybrid_forward(self, F, x):
      c3, c4 = self.base_forward(x)
  
      x = self.head(c4)
      x = list(x)
      x[0] = F.contrib.BilinearResize2D(x[0], **self._up_kwargs)
      x[1] = F.contrib.BilinearResize2D(x[1], **self._up_kwargs)
      x[2] = F.contrib.BilinearResize2D(x[2], **self._up_kwargs)
  
      outputs = [x[0]]
      outputs.append(x[1])
      outputs.append(x[2])
  
      return tuple(outputs)
  
file_path: gluon-cv/gluoncv/model_zoo/danet.py
imports: from mxnet.gluon import nn
  from mxnet.context import cpu
  from mxnet.gluon.nn import HybridBlock
  from .segbase import SegBaseModel
  from .fcn import _FCNHead
  from .attention import PAM_Module, CAM_Module
label_desc: Use image node_id 2 for calling the DANet obj's underlying member method code with example usage: obj.hybrid_forward(F, x) and returns: tuple